Enhancing Membrane Protein Identification Using a Simplified Centrifugation and Detergent-Based Membrane Extraction Approach

Metal organic layers enabled cell surface engineering coupling biomembrane fusion for dynamic membrane proteome profiling

Systematically dissecting the highly dynamic and tightly communicating membrane proteome of living cells is essential for the system-level understanding of fundamental cellular processes and intricate relationship between membrane-bound organelles constructed through membrane traffic. While extensive efforts have been made to enrich membrane proteins, their comprehensive analysis with high selectivity and deep coverage remains a challenge, especially at the living cell state. To address this problem, we developed the cell surface engineering coupling biomembrane fusion method to map the whole membrane proteome from the plasma membrane to various organelle membranes taking advantage of the exquisite interaction between two-dimensional metal-organic layers and phospholipid bilayers on the membrane. This approach, which bypassed conventional biochemical fractionation and ultracentrifugation, facilitated the enrichment of membrane proteins in their native phospholipid bilayer environment, helping to map the membrane proteome with a specificity of 77% and realizing the deep coverage of the HeLa membrane proteome (5087 membrane proteins). Furthermore, membrane N-phosphoproteome was profiled by integrating the N-phosphoproteome analysis strategy, and the dynamic membrane proteome during apoptosis was deciphered in combination with quantitative proteomics. The features of membrane protein N-phosphorylation modifications and many differential proteins during apoptosis associated with mitochondrial dynamics and ER homeostasis were found. The method provided a simple and robust strategy for efficient analysis of membrane proteome, offered a reliable platform for research on membrane-related cell dynamic events and expanded the application of metal-organic layers.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Cell Surface Engineering Enables Surfaceome Profiling

Cell surface proteins (CSPs) are vital molecular mediators for cells and their extracellular environment. Thus, understanding which CSPs are displayed on cells, especially in different cell states, remains an important endeavor in cell biology. Here, we describe the integration of cell surface engineering with radical-mediated protein biotinylation to profile CSPs. This method relies on the prefunctionalization of cells with cholesterol lipid groups, followed by sortase-catalyzed conjugation with an APEX2 ascorbate peroxidase enzyme. In the presence of biotin-phenol and H₂O₂, APEX2 catalyzes the formation of highly reactive biotinyl radicals that covalently tag electron-rich residues within CSPs for subsequent streptavidin-based enrichment and analysis by quantitative mass spectrometry. While APEX2 is traditionally used to capture proximity-based interactomes, we envisioned using it in a "baitless" manner on cell surfaces to capture CSPs. We evaluate this strategy in light of another CSP labeling method that relies on the presence of cell surface sialic acid. Using the APEX2 strategy, we describe the CSPs found in three mammalian cell lines and compare CSPs in adherent versus three-dimensional pancreatic adenocarcinoma cells.

Bioorthogonal Conjugation-Assisted Purification Method for Profiling Cell Surface Proteome

Surface biotinylation has been widely adapted in profiling the cellular proteome associated with the plasma membrane. However, the workflow is subject to interference from the cytoplasmic biotin-associated proteins that compete for streptavidin-binding during purification. Here we established a bioorthogonal conjugation-assisted purification (BCAP) workflow that utilizes the Staudinger chemoselective ligation to label and isolate surface-associated proteins while minimizing the binding of endogenous biotin-associated proteins. Label-free quantitative proteomics demonstrated that BCAP is efficient in isolating cell surface proteins with excellent reproducibility. Subsequently, we applied BCAP to compare the surface proteome of proliferating and senescent mouse embryonic fibroblasts (MEFs). Among the results, EHD2 was identified and validated as a novel protein that is enhanced at the cell surface of senescent MEFs. We expect that BCAP will have broad applications in profiling cell surface proteomes in the future.

Differential Detergent Fractionation of Membrane Protein From Small Samples of Hepatocytes and Liver Tissue for Quantitative Proteomic Analysis of Drug Metabolizing Enzymes and Transporters

The fractionation of enough membrane protein from limited samples is challenging for MS-based quantitative targeted absolute proteomics (QTAP) of drug metabolizing enzymes (DMEs) and transporters. This study evaluated differential detergent fractionation (DDF) of membrane protein from progressively smaller numbers of primary mouse hepatocytes (5 million down to 50,000 cells) and limited liver tissue (25-50 mg) in quantifying select DMEs and transporters by QTAP. Two non-ionic detergents, digitonin and Triton-X-100, were applied in sequence to permeabilize cells and extract membrane proteins. Comparison was made with a membrane protein extraction kit and with homogenization in hypotonic buffer and subsequent differential centrifugation (DC). DDF produced linear membrane protein yields with increasing hepatocyte numbers and better permeabilization evidenced by the higher ratio of cytosolic to membrane protein yields. DDF produced 5-times more membrane protein from liver tissue than DC. The concentration of DMEs and transporters remained consistent in the fractions prepared by DDF from progressively smaller numbers of hepatocytes, but declined in kit fractions. In liver tissue, the concentrations were comparatively higher in DDF versus kit and DC. In conclusion, sequential digitonin and Triton-X-100 fractionation of membrane protein from limited samples is efficient, reproducible and cost-effective for QTAP of DMEs and transporters.

An overview on enrichment methods for cell surface proteome profiling

Cell surface proteins are essential for many important biological processes, including cell-cell interactions, signal transduction, and molecular transportation. With the characteristics of low abundance, high hydrophobicity, and high heterogeneity, it is difficult to get a comprehensive view of cell surface proteome by direct analysis. Thus, it is important to selectively enrich the cell surface proteins before liquid chromatography with mass spectrometry analysis. In recent years, a variety of enrichment methods have been developed. Based on the separation mechanism, these methods could be mainly classified into three types. The first type is based on their difference in the physicochemical property, such as size, density, charge, and hydrophobicity. The second one is based on the bimolecular affinity interaction with lectin or antibody. And the third type is based on the chemical covalent coupling to free side groups of surface-exposed proteins or carbohydrate chains, such as primary amines, carboxyl groups, glycan side chains. In addition, metabolic labeling and enzymatic reaction-based methods have also been employed to selectively isolate cell surface proteins. In this review, we will provide a comprehensive overview of the enrichment methods for cell surface proteome profiling.

Sensitive profiling of cell surface proteome by using an optimized biotinylation method

Cell surface proteins are responsible for many critical functions. Systematical profiling of these proteins would provide a unique molecular fingerprint to classify cells and provide important information to guide immunotherapy. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of cells. When this protocol was combined with a tip based fractionation scheme, 4510 proteins, including 2055 annotated cell surface-associated proteins, were identified with only 20 microgram protein digest, showing the superior sensitivity of the approach. To enable process 10 times fewer cells, a pipet tip based protocol was developed, which led to the identification of about 600 cell surface-associated proteins. Finally, the new protocol was applied to compare the cell surface proteomes of two breast cancer cell lines, BT474 and MCF7. It was found that many cell surface-associated proteins were differentially expressed. The new protocols were demonstrated to be easy to perform, time-saving, and yielding good selectivity and high sensitivity. We expect this protocol would have broad applications in the future. SIGNIFICANCE: Cell surface proteins confer specific cellular functions and are easily accessible. They are often used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Thus, efficient methods for profiling cell surface proteins are highly demanded. Cell surface biotinylation method is one of the effective methods for cell surface proteome profiling. However, classical workflows suffer the disadvantage of poor sensitivity. In this work, we presented an optimized protocol which enabled identification of more cell surface proteins from a smaller number of starting cells. The new protocol is easier to perform, time-saving and has less protein loss. By using a special pipet tip, sensitive and in-depth cell surface proteome analysis could be achieved. In combination with label-free quantitative MS, the new protocol can be applied to the differential analysis of the cell surface proteomes between different cell lines to find genetically- or drug-induced changes. We expect this protocol would have broad application in cell surface protein studies, including the discovery of diagnostic marker proteins and potential therapeutic targets.

FractionOptimizer: a method for optimal peptide fractionation in bottom-up proteomics

Recent advances in mass spectrometry and separation technologies created the opportunities for deep proteome characterization using shotgun proteomics approaches. The "real world" sample complexity and high concentration range limit the sensitivity of this characterization. The common strategy for increasing the sensitivity is sample fractionation prior to analysis either at the protein or the peptide level. Typically, fractionation at the peptide level is performed using linear gradient high-performance liquid chromatography followed by uniform fraction collection. However, this way of peptide fractionation results in significantly suboptimal operation of the mass spectrometer due to the non-uniform distribution of peptides between the fractions. In this work, we propose an approach based on peptide retention time prediction allowing optimization of chromatographic conditions and fraction collection procedures. An open-source software implementing the approach called FractionOptimizer was developed and is available at http://hg.theorchromo.ru/FractionOptimizer . The performance of the developed tool was demonstrated for human embryonic kidney (HEK293) cell line lysate. In these experiments, we improved the uniformity of the peptides distribution between fractions. Moreover, in addition to 13,492 peptides, we found 6787 new peptides not identified in the experiments without fractionation and up to 800 new proteins (or 25%). Graphical abstract The analysis workflow employing FractionOptimizer software.